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In this paper, we introduce an efficient backpropagation scheme for non-constrained implicit functions.
Generalization of Back propagation to Recurrent and Higher Order Neural Networks
F. J. Pineda · 1988
Earlier work this paper cites.
A Learning Rule for Asynchronous Perceptrons with Feedback in a Combinatorial Environment
L. B. Almeida · 1990
Earlier work this paper cites.
Solving Ordinary Differential Equations II: Stiff and Differential-Algebraic Problems
E. Hairer, S. P. Nørsett, and G. Wanner · 1993
Earlier work this paper cites.
An Introduction to the Conjugate Gradient Method Without the Agonizing Pain
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Earlier work this paper cites.
A Framework for Behavioural Cloning
M. Bain and C. Sammut · 1996
Earlier work this paper cites.
Inexact Preconditioned Conjugate Gradient Method with Inner-Outer Iteration
G. H. Golub and Q. Ye · 1999
Earlier work this paper cites.
Numerical Methods for Ordinary Differential Equations
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Earlier work this paper cites.
Iterative Methods for Sparse Linear Systems
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Earlier work this paper cites.
A survey of numerical methods for optimal control
A. V. Rao · 2009
Earlier work this paper cites.
Numerical Optimal Control
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Earlier work this paper cites.
Nonsymmetric Preconditioning for Conjugate Gradient and Steepest Descent Methods
H. Bouwmeester, A. Dougherty, and A. V. Knyazev · 2015
Earlier work this paper cites.
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Task-based End-to-end Model Learning in Stochastic Optimization
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L. E. Ghaoui, F. Gu, B. Travacca, and A. Askari · 2019
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ANODE: Unconditionally Accurate Memory-Efficient Gradients for NeuralODEs
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Deep Declarative Networks: A New Hope
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A tour of reinforcement learning: The view from continuous control
B. Recht · 2019
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Generative Adversarial Imitation from Observation
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SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver
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Behavioral Cloning from Observation
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Z. Zhang, A. Kag, A. Sullivan, and V. Saligrama · 2018
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Differentiable Convex Optimization Layers
A. Agrawal, B. Amos, S. Barratt, S. Boyd, S. Diamond, and J. Z. Kolter · 2019
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Deep Equilibrium Models
S. Bai, J. Z. Kolter, and V. Koltun · 2019
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Neural Networks with Cheap Differential Operators
T. Q. Chen and D. Duvenaud · 2019
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P. Wang, P. L. Donti, B. Wilder, and J. Z. Kolter · 2019
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ODE2VAE: Deep generative second order ODEs with Bayesian neural networks
C. Yildiz, M. Heinonen, and H. Lähdesmäki · 2019
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The Differentiable Cross-Entropy Method
B. Amos and D. Yarats · 2020
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Infinite-Horizon Differentiable Model Predictive Control
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Implicitly defined layers in neural networks
Q. Zhang, Y. Gu, M. Mateusz, M. Baktashmotlagh, and A. Eriksson · 2020
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